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Growth of industrial CO2 emissions in Shanghai city: Evidence from a dynamic vector autoregression analysis

Boqiang Lin () and Bin Xu

Energy, 2018, vol. 151, issue C, 167-177

Abstract: Carbon dioxide (CO2) is one of the main sources of global warming, rising sea levels, and frequent outbreaks of extreme weather. China is now one of the largest energy consumer and CO2 emitters in the world. As one of China's economic centers, Shanghai city has a perfect industrial system with large industrial scale. The industrial sector is an energy– and emission–intensive industry, which contributes the significant part of CO2 emissions in Shanghai city. Therefore, an in–depth investigation of the main driving forces of CO2 emissions in the industrial sector is essential to reduce CO2 emissions in the city. This study uses Vector Autoregressive model to analyze the main factors causing the increase in CO2 emissions in the industrial sector. The results show that economic growth leads to an increase in CO2 emissions in the short run, but is conducive to reducing CO2 emissions in the long run, due to the differences in fixed–asset investment and export trade. Energy consumption structure leads to a growing CO2 emissions in the short term, and is beneficial to mitigate CO2 emissions in the long term, owing to the gradual optimization of energy consumption structure. However, urbanization helps to reduce CO2 emissions in the short term, but leads to an increase in CO2 emissions in the long term, because of urban real estate and infrastructure construction investments as well as vehicle use. Energy efficiency leads to an increase in CO2 emissions both in the short and long run since the scale effect exceeds the technical effect. Industrial structure produces a positive effect in the short run, but the impact is gradually narrowing in the long run.

Keywords: The industrial sector; Carbon dioxide emissions; Vector autoregression model (search for similar items in EconPapers)
Date: 2018
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